Since DTCS can be used with any table, it is important to know when it is a good idea, and when it is not. I’ll try to explain the spectrum and trade-offs here:

1. Perfect Fit: Time Series Fact Data, Deletes by Default TTL: When you ingest fact data that is ordered in time, with no deletes or overwrites. This is the standard “time series” use case.

2. OK Fit: Time-Ordered, with limited updates across whole data set, or only updates to recent data: When you ingest data that is (mostly) ordered in time, but revise or delete a very small proportion of the overall data across the whole timeline.

3. Not a Good Fit: many partial row updates or deletions over time: When you need to partially revise or delete fields for rows that you read together. Also, when you revise or delete rows within clustered reads.